AGU Fall Meeting 2016December 12-16, 2016San Francisco, CA

Presented by: Keith SawiczAbstract:Modelling approaches to transfer hydrologically-relevant information from locations with streamflow measurements to locations without such measurements continues to be an active field of research for hydrologists. The Pacific Northwest Hydrologic Landscapes (PNW HL) provide a solid conceptual classification framework based on our understanding of dominant processes. A Hydrologic Landscape code (5 letter descriptor based on physical and climatic properties) describes each assessment unit area, and these units average area 60km2. The core function of these HL codes is to relate and transfer hydrologically meaningful information between watersheds without the need for streamflow time series. We present a novel approach based on the HL framework to answer the question “How can we calibrate models across separate watersheds simultaneously, guided by our understanding of dominant processes?“. We should be able to apply the same parameterizations to assessment units of common HL codes if 1) the Hydrologic Landscapes contain hydrologic information transferable between watersheds at a sub-watershed-scale and 2) we use a conceptual hydrologic model and parameters that reflect the hydrologic behavior of a watershed. In this study, This work specifically tests the ability or inability to use HL-codes to inform and share model parameters across watersheds in the Pacific Northwest.

Presented by: Chas JonesAbstract:Identifying regions with similar hydrology is useful for assessing water quality and quantity across the U.S., especially areas that are difficult or costly to monitor. For example, hydrologic landscapes (HLs) have been used to map streamflow variability and assess the spatial distribution of climatic response in Oregon, Alaska, and the Pacific Northwest. HLs have also been applied to assess historic and projected climatic impacts across the Western U.S. In this project, we summarized (1) the HL classification methodology and (2) the utility of using HLs as a tool to classify the vulnerability of streams to climatic changes in the Western U.S. During the HL classification process, we analyzed climate, seasonality, aquifer permeability, terrain, and soil permeability as the primary hydrologic drivers (and precipitation intensity as a secondary driver) associated with large scale hydrologic processes (storage, conveyance, and flow of water into or out of the watershed) in the West. We derived the dominant hydrologic pathways (surface runoff or deep or shallow groundwater) from the HL classification of different catchments to test our hypotheses: 1) Changes in climate will have greater impacts on streamflow in catchments dominated by surface runoff. 2) Catchments historically fed by surface runoff from winter snowmelt in the spring will experience greater impact if precipitation falls as rain instead of snow. We calculated S* (precipitation surplus, which includes snowmelt runoff) as a proxy for streamflow for watersheds across the landscape under historic (1901-2000), modern (1971-2000), and future climate projections (2041-2070) to determine whether future projections of S* fall outside of the range of historic S*. Catchments with projections outside the historic range may be more vulnerable to changes in streamflow. Our results indicate that streams dominated by surface runoff and catchments with spring seasonality are more vulnerable to climatic changes. This approach can be used to identify streams that are vulnerable to changes in streamflow and associated reductions is water quality, which are of important for the ecological function of aquatic ecosystems throughout the U.S.